An approach to semi-supervised learning is proposed that is based on a Gaussian random field model. Labeled and unlabeled data are represented as vertices in a weighted graph, wit...
This study develops a procedure for automatic extraction and segmentation of a class-specific object (or region) by learning class-specific boundaries. We present and evaluate t...
In this paper, we present a dependency treebased method for sentiment classification of Japanese and English subjective sentences using conditional random fields with hidden varia...
We develop nonparametric Bayesian models for multiscale representations of images depicting natural scene categories. Individual features or wavelet coefficients are marginally de...
Jyri J. Kivinen, Erik B. Sudderth, Michael I. Jord...
We address document image classification by visual appearance. An image is represented by a variable-length list of visually salient features. A hierarchical Bayesian network is ...